blakeblackshear.frigate/.cspell/frigate-dictionary.txt

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aarch
absdiff
airockchip
Alloc
License plate recognition (ALPR) backend (#14564) * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * config * config * lpr maintainer * clean up * clean up * fix processing * don't process for stationary cars * fix order * fixes * check for known plates * improved length and character by character confidence * model fixes and small tweaks * docs * placeholder for non frigate+ model lp detection --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-10-26 19:07:45 +02:00
alpr
2024-05-20 15:37:56 +02:00
Amcrest
amdgpu
analyzeduration
Annke
apexcharts
arange
argmax
argmin
argpartition
ascontiguousarray
astype
authelia
authentik
autodetected
automations
autotrack
autotracked
autotracker
autotracking
balena
2024-05-20 15:37:56 +02:00
Beelink
BGRA
BHWC
blackshear
2024-05-20 15:37:56 +02:00
blakeblackshear
bottombar
buildx
castable
cdist
Celeron
cgroups
chipset
chromadb
Chromecast
cmdline
codeowner
CODEOWNERS
2024-05-20 15:37:56 +02:00
codeproject
colormap
colorspace
comms
Add service manager infrastructure (#14150) * Add service manager infrastructure The changes are (This will be a bit long): - A ServiceManager class that spawns a background thread and deals with service lifecycle management. The idea is that service lifecycle code will run in async functions, so a single thread is enough to manage any (reasonable) amount of services. - A Service class, that offers start(), stop() and restart() methods that simply notify the service manager to... well. Start, stop or restart a service. (!) Warning: Note that this differs from mp.Process.start/stop in that the service commands are sent asynchronously and will complete "eventually". This is good because it means that business logic is fast when booting up and shutting down, but we need to make sure that code does not rely on start() and stop() being instant (Mainly pid assignments). Subclasses of the Service class should use the on_start and on_stop methods to monitor for service events. These will be run by the service manager thread, so we need to be careful not to block execution here. Standard async stuff. (!) Note on service names: Service names should be unique within a ServiceManager. Make sure that you pass the name you want to super().__init__(name="...") if you plan to spawn multiple instances of a service. - A ServiceProcess class: A Service that wraps a multiprocessing.Process into a Service. It offers a run() method subclasses can override and can support in-place restarting using the service manager. And finally, I lied a bit about this whole thing using a single thread. I can't find any way to run python multiprocessing in async, so there is a MultiprocessingWaiter thread that waits for multiprocessing events and notifies any pending futures. This was uhhh... fun? No, not really. But it works. Using this part of the code just involves calling the provided wait method. See the implementation of ServiceProcess for more details. Mirror util.Process hooks onto service process Remove Service.__name attribute Do not serialize process object on ServiceProcess start. asd * Update frigate dictionary * Convert AudioProcessor to service process
2024-10-21 17:00:38 +02:00
coro
ctypeslib
CUDA
Cuvid
Dahua
2024-05-20 15:37:56 +02:00
datasheet
debconf
deci
deepstack
defragment
2024-05-20 15:37:56 +02:00
devcontainer
DEVICEMAP
discardcorrupt
dpkg
dsize
dtype
ECONNRESET
edgetpu
License plate recognition (ALPR) backend (#14564) * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * config * config * lpr maintainer * clean up * clean up * fix processing * don't process for stationary cars * fix order * fixes * check for known plates * improved length and character by character confidence * model fixes and small tweaks * docs * placeholder for non frigate+ model lp detection --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-10-26 19:07:45 +02:00
facenet
Add service manager infrastructure (#14150) * Add service manager infrastructure The changes are (This will be a bit long): - A ServiceManager class that spawns a background thread and deals with service lifecycle management. The idea is that service lifecycle code will run in async functions, so a single thread is enough to manage any (reasonable) amount of services. - A Service class, that offers start(), stop() and restart() methods that simply notify the service manager to... well. Start, stop or restart a service. (!) Warning: Note that this differs from mp.Process.start/stop in that the service commands are sent asynchronously and will complete "eventually". This is good because it means that business logic is fast when booting up and shutting down, but we need to make sure that code does not rely on start() and stop() being instant (Mainly pid assignments). Subclasses of the Service class should use the on_start and on_stop methods to monitor for service events. These will be run by the service manager thread, so we need to be careful not to block execution here. Standard async stuff. (!) Note on service names: Service names should be unique within a ServiceManager. Make sure that you pass the name you want to super().__init__(name="...") if you plan to spawn multiple instances of a service. - A ServiceProcess class: A Service that wraps a multiprocessing.Process into a Service. It offers a run() method subclasses can override and can support in-place restarting using the service manager. And finally, I lied a bit about this whole thing using a single thread. I can't find any way to run python multiprocessing in async, so there is a MultiprocessingWaiter thread that waits for multiprocessing events and notifies any pending futures. This was uhhh... fun? No, not really. But it works. Using this part of the code just involves calling the provided wait method. See the implementation of ServiceProcess for more details. Mirror util.Process hooks onto service process Remove Service.__name attribute Do not serialize process object on ServiceProcess start. asd * Update frigate dictionary * Convert AudioProcessor to service process
2024-10-21 17:00:38 +02:00
fastapi
faststart
fflags
2024-05-20 15:37:56 +02:00
ffprobe
fillna
flac
foscam
2024-05-20 15:37:56 +02:00
fourcc
framebuffer
fregate
frégate
fromarray
frombuffer
2024-05-20 15:37:56 +02:00
frontdoor
fstype
fullchain
fullscreen
genai
generativeai
genpts
getpid
gpuload
2024-05-20 15:37:56 +02:00
HACS
Hailo
2024-05-20 15:37:56 +02:00
hass
hconcat
healthcheck
hideable
Hikvision
homeassistant
homekit
homography
hsize
hstack
httpx
hwaccel
hwdownload
hwmap
hwupload
iloc
imagestream
imdecode
imencode
imread
imutils
imwrite
interp
iostat
2024-05-20 15:37:56 +02:00
iotop
itemsize
Jellyfin
jetson
jetsons
License plate recognition (ALPR) backend (#14564) * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * config * config * lpr maintainer * clean up * clean up * fix processing * don't process for stationary cars * fix order * fixes * check for known plates * improved length and character by character confidence * model fixes and small tweaks * docs * placeholder for non frigate+ model lp detection --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-10-26 19:07:45 +02:00
jina
jinaai
joserfc
jsmpeg
jsonify
Kalman
keepalive
keepdims
labelmap
2024-05-20 15:37:56 +02:00
letsencrypt
levelname
LIBAVFORMAT
libedgetpu
libnvinfer
libva
libwebp
libx
libyolo
linalg
localzone
logpipe
Loryta
lstsq
2024-05-20 15:37:56 +02:00
lsusb
markupsafe
maxsplit
MEMHOSTALLOC
memlimit
meshgrid
metadatas
migraphx
minilm
mjpeg
mkfifo
mobiledet
mobilenet
modelpath
mosquitto
mountpoint
movflags
mpegts
mqtt
mse
msenc
namedtuples
nbytes
nchw
ndarray
ndimage
nethogs
newaxis
nhwc
NOBLOCK
nobuffer
nokey
NONBLOCK
noninteractive
noprint
Norfair
nptype
NTSC
numpy
nvenc
nvhost
nvml
nvmpi
ollama
onnx
onnxruntime
onvif
ONVIF
openai
opencv
openvino
OWASP
License plate recognition (ALPR) backend (#14564) * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * config * config * lpr maintainer * clean up * clean up * fix processing * don't process for stationary cars * fix order * fixes * check for known plates * improved length and character by character confidence * model fixes and small tweaks * docs * placeholder for non frigate+ model lp detection --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-10-26 19:07:45 +02:00
paddleocr
paho
2024-05-20 15:37:56 +02:00
passwordless
popleft
posthog
postprocess
2024-05-20 15:37:56 +02:00
poweroff
preexec
probesize
protobuf
pstate
psutil
pubkey
putenv
pycache
pydantic
pyobj
pysqlite
pytz
pywebpush
2024-05-20 15:37:56 +02:00
qnap
quantisation
Radeon
radeonsi
radeontop
rawvideo
rcond
RDONLY
2024-05-20 15:37:56 +02:00
rebranded
referer
reindex
Reolink
restream
restreamed
restreaming
rkmpp
rknn
rkrga
rockchip
rocm
rocminfo
rootfs
rtmp
RTSP
ruamel
scroller
setproctitle
setpts
shms
SIGUSR
skylake
sleeptime
SNDMORE
socs
sqliteq
Add service manager infrastructure (#14150) * Add service manager infrastructure The changes are (This will be a bit long): - A ServiceManager class that spawns a background thread and deals with service lifecycle management. The idea is that service lifecycle code will run in async functions, so a single thread is enough to manage any (reasonable) amount of services. - A Service class, that offers start(), stop() and restart() methods that simply notify the service manager to... well. Start, stop or restart a service. (!) Warning: Note that this differs from mp.Process.start/stop in that the service commands are sent asynchronously and will complete "eventually". This is good because it means that business logic is fast when booting up and shutting down, but we need to make sure that code does not rely on start() and stop() being instant (Mainly pid assignments). Subclasses of the Service class should use the on_start and on_stop methods to monitor for service events. These will be run by the service manager thread, so we need to be careful not to block execution here. Standard async stuff. (!) Note on service names: Service names should be unique within a ServiceManager. Make sure that you pass the name you want to super().__init__(name="...") if you plan to spawn multiple instances of a service. - A ServiceProcess class: A Service that wraps a multiprocessing.Process into a Service. It offers a run() method subclasses can override and can support in-place restarting using the service manager. And finally, I lied a bit about this whole thing using a single thread. I can't find any way to run python multiprocessing in async, so there is a MultiprocessingWaiter thread that waits for multiprocessing events and notifies any pending futures. This was uhhh... fun? No, not really. But it works. Using this part of the code just involves calling the provided wait method. See the implementation of ServiceProcess for more details. Mirror util.Process hooks onto service process Remove Service.__name attribute Do not serialize process object on ServiceProcess start. asd * Update frigate dictionary * Convert AudioProcessor to service process
2024-10-21 17:00:38 +02:00
sqlitevecq
ssdlite
statm
stimeout
stylelint
subclassing
substream
superfast
surveillance
svscan
Swipeable
sysconf
tailscale
Tapo
tensorrt
tflite
thresholded
timelapse
tmpfs
tobytes
toggleable
traefik
tzlocal
Ubiquiti
udev
2024-05-20 15:37:56 +02:00
udevadm
ultrafast
unichip
unidecode
Unifi
unixepoch
2024-05-20 15:37:56 +02:00
unraid
unreviewed
userdata
usermod
Add service manager infrastructure (#14150) * Add service manager infrastructure The changes are (This will be a bit long): - A ServiceManager class that spawns a background thread and deals with service lifecycle management. The idea is that service lifecycle code will run in async functions, so a single thread is enough to manage any (reasonable) amount of services. - A Service class, that offers start(), stop() and restart() methods that simply notify the service manager to... well. Start, stop or restart a service. (!) Warning: Note that this differs from mp.Process.start/stop in that the service commands are sent asynchronously and will complete "eventually". This is good because it means that business logic is fast when booting up and shutting down, but we need to make sure that code does not rely on start() and stop() being instant (Mainly pid assignments). Subclasses of the Service class should use the on_start and on_stop methods to monitor for service events. These will be run by the service manager thread, so we need to be careful not to block execution here. Standard async stuff. (!) Note on service names: Service names should be unique within a ServiceManager. Make sure that you pass the name you want to super().__init__(name="...") if you plan to spawn multiple instances of a service. - A ServiceProcess class: A Service that wraps a multiprocessing.Process into a Service. It offers a run() method subclasses can override and can support in-place restarting using the service manager. And finally, I lied a bit about this whole thing using a single thread. I can't find any way to run python multiprocessing in async, so there is a MultiprocessingWaiter thread that waits for multiprocessing events and notifies any pending futures. This was uhhh... fun? No, not really. But it works. Using this part of the code just involves calling the provided wait method. See the implementation of ServiceProcess for more details. Mirror util.Process hooks onto service process Remove Service.__name attribute Do not serialize process object on ServiceProcess start. asd * Update frigate dictionary * Convert AudioProcessor to service process
2024-10-21 17:00:38 +02:00
uvicorn
vaapi
vainfo
variations
vbios
vconcat
vitb
vstream
vsync
wallclock
webp
webpush
webrtc
websockets
webui
werkzeug
workdir
WRONLY
wsgirefserver
wsgiutils
wsize
xaddr
xmaxs
xmins
XPUB
XSUB
ymaxs
ymins
yolo
yolonas
yolox
zeep
License plate recognition (ALPR) backend (#14564) * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * config * config * lpr maintainer * clean up * clean up * fix processing * don't process for stationary cars * fix order * fixes * check for known plates * improved length and character by character confidence * model fixes and small tweaks * docs * placeholder for non frigate+ model lp detection --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-10-26 19:07:45 +02:00
zerolatency